The method of parametric adaptation of the check polynomials of the component recursive systematic convulsion code turbo code
DOI:
https://doi.org/10.32347/2411-4049.2024.2.157-172Keywords:
corrective codes, turbo codes, wireless data transmission systems, likelihood functions, adaptationAbstract
The article is devoted to increasing the efficiency of the functioning of wireless information transmission systems due to the adaptation of the verification polynomials of the component recursive systematic convolutional turbo code by solving the optimization problem using the gradient method. After the appearance of the extremely important work of K. Shannon, huge efforts have been made to find new transmission methods in order to approach the bandwidth of the channel. Channel coding is one of the main methods that enables such operation at almost full bandwidth. The probability of a white error of information decoding is chosen as the objective function. To calculate the probability of a bit error in information decoding, it is proposed to use cyclic codes. Adaptation schemes of these codes are used to improve the characteristics of information reliability. At the same time, during adaptation, in the vast majority of works, only one parameter changes – the coding speed, which does not fully increase the effectiveness of corrective coding schemes. The purpose of the article is to increase the efficiency of wireless information transmission systems by adapting the verification polynomials of the component recursive systematic convolutional turbo code by solving the optimization problem. The article consists of an introduction, which highlights the problem, analyzes the latest research and publications on this topic, and formulates the purpose of the article. The results of the research are shown, conclusions and prospects for further research are drawn. The article ends with a list of used sources. As a result of the proposed method, the effective number of verification polynomials of the RSCC turbo code, which were found using the method for the channel with additive white Gaussian noise for different sizes of the input data block, is given. We consider the direction of further research to expand the search range to take into account a larger number of parameters of turbo codes during adaptation, while the following can be foreseen: the number of bits in a block, types of interleavers, decoding algorithms, decoding iterations, etc.
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